Staff Product Engineer - GenAI, AI/ML & Data Analytics

About the role

Micron Technology, a leader in memory and storage solutions, is hiring a Staff Product Engineer within its HIG HBM Product Engineering organization. You will help develop next-generation GenAI, machine learning and advanced data analytics solutions for semiconductor engineering, working with cross-functional teams to prototype, build and scale AI-driven solutions that improve quality, cost, cycle time and engineering efficiency.

Key responsibilities

• Design, build and improve GenAI-powered and agentic systems for semiconductor workflows such as code generation, data extraction, analytics, documentation automation, failure triage and technical knowledge retrieval.
• Develop scalable data pipelines and analytical workflows to ingest, clean, transform and analyze large, heterogeneous datasets from manufacturing and engineering systems.
• Use Python, SQL and data science libraries (e.g. pandas, matplotlib) to perform deep analysis and generate visualizations.
• Build, evaluate and optimize LLM workflows, including prompting, RAG, inference orchestration, benchmarking and quality evaluation.
• Develop and productionize machine learning and deep learning models for classification, regression, anomaly detection, failure analysis and engineering decision support.
• Implement distributed data processing techniques such as data cleansing, outlier detection and missing-data handling with frameworks such as PySpark and BigQuery.
• Collaborate with domain experts and cross-functional teams, and support deployment, monitoring and operationalization of AI/ML solutions in cloud and enterprise environments.
• Communicate technical findings and model outcomes to technical and non-technical stakeholders, and identify high-impact opportunities to improve engineering productivity.

Required profile

• Bachelor's or Master's degree in Electrical Engineering, Computer Science, Data Science, Statistics, Artificial Intelligence or a related field.
• At least 2 years of hands-on experience developing and deploying AI applications in semiconductors, electronics or other engineering industries.
• Experience with LLM training, inference and evaluation workflows, including prompt design, benchmarking and retrieval-augmented systems.
• Experience analyzing large, complex datasets and applying data cleansing, outlier handling and missing-data treatment.
• Preferred: experience building agentic systems for semiconductor manufacturing, product engineering, validation, yield improvement, reliability or failure analysis, and experience in cross-functional engineering, manufacturing, data science and IT environments.

Required skills

• Strong Python and SQL proficiency.
• Data analytics and visualization with tools such as pandas, scikit-learn, matplotlib, plotly or similar.
• Familiarity with agentic AI frameworks such as LangGraph, Google ADK, AutoGen and evaluation tools such as AgentEval.
• Familiarity with modern AI coding tools such as Claude Code, Roo Code, Cursor, Cline, Windsurf, Gemini CLI or similar.
• Hands-on experience with LLMs, RAG, agentic workflows and frameworks such as PyTorch or TensorFlow.
• Cloud experience with GCP, AWS or Azure, including deploying ML pipelines in production.
• Preferred: enterprise data platforms (BigQuery, Snowflake, MSSQL, Oracle, Redshift), Kubernetes, web technologies (JavaScript, HTML, CSS), and deep learning architectures and computer vision.